SARS-CoV-2, influenza A/B and respiratory syncytial virus positivity and association with influenza-like illness and self-reported symptoms, over the 2022/23 winter season in the UK: a longitudinal surveillance cohort (preprint)

Background Syndromic surveillance often relies on patients presenting to healthcare. Community cohorts, although more challenging to recruit, could provide additional population-wide insights, particularly with SARS-CoV-2 co-circulating with other respiratory viruses. Methods We estimated positivity and incidence of SARS-CoV-2, influenza A/B, and RSV, and trends in self-reported symptoms including influenza-like illness (ILI), over the 2022/23 winter season in a broadly representative UK community cohort (COVID-19 Infection Survey), using negative-binomial generalised additive models. We estimated associations between test positivity and each of symptoms and influenza vaccination, using adjusted logistic and multinomial models. Findings Swabs taken at 32,937/1,352,979 (2.4%) assessments tested positive for SARS-CoV-2, 181/14,939 (1.2%) for RSV and 130/14,939 (0.9%) for influenza A/B, varying by age over time. Positivity and incidence peaks were earliest for RSV, then influenza A/B, then SARS-CoV-2, and were highest for RSV in the youngest and for SARS-CoV-2 in the oldest age-groups. Many test-positives did not report key symptoms: middle-aged participants were generally more symptomatic than older or younger participants, but still only ~25% reported ILI-WHO and ~60% ILI-ECDC. Most symptomatic participants did not test positive for any of the three viruses. Influenza A/B-positivity was lower in participants reporting influenza vaccination in the current and previous seasons (odds ratio=0.55 (95% CI 0.32,0.95)) versus neither season. Interpretation Symptom profiles varied little by aetiology, making distinguishing SARS-CoV-2, influenza and RSV using symptoms challenging. Most symptoms were not explained by these viruses, indicating the importance of other pathogens in syndromic surveillance. Influenza vaccination was associated with lower rates of community influenza test positivity. Funding UK Health Security Agency, Department of Health and Social Care, National Institute for Health Research.

Risk of SARS-CoV-2 reinfection during multiple Omicron variant waves in the UK general population (preprint)

SARS-CoV-2 reinfections increased substantially after Omicron variants emerged. Large-scale community-based comparisons across multiple Omicron waves of reinfection characteristics, risk factors, and protection afforded by previous infection and vaccination, are limited, especially after widespread national testing stopped. We studied 245,895 adults >=18y in the UK's national COVID-19 Infection Survey with at least one infection (identified from positive swab tests done within the study, linked from national testing programmes, or self-reported by participants, up to their last study assessment). We quantified the risk of reinfection in multiple infection waves, including those driven by BA.1, BA.2, BA.4/5, and most recently BQ.1/CH.1.1/XBB.1.5 variants, in which most reinfections occurred. Reinfections had higher cycle threshold (Ct) values (lower viral load) and lower percentages self-reporting symptoms compared with first infections. Across multiple Omicron waves, protection against reinfection was significantly higher in those previously infected with more recent than earlier variants, even at the same time from previous infection. Protection against Omicron reinfections decreased over time from the most recent infection if this was the previous or penultimate variant (generally within the preceding year), but did not change or even slightly increased over time if this was with an even earlier variant (generally >1 year previously). Those 14-180 days after receiving their most recent vaccination had a lower risk of reinfection with all Omicron variants except BA.2 than those >180 days from their most recent vaccination. Reinfection risk was independently higher in those aged 30-45 years, and with either low or high Ct values in their most recent previous infection. Overall, the risk of Omicron reinfection is high, but with lower severity than first infections; reinfection risk is likely driven as much by viral evolution as waning immunity.

Improving the representativeness of UKs national COVID-19 Infection Survey through spatio-temporal regression and post-stratification (preprint)

Population-representative estimates of SARS-CoV-2 infection prevalence and antibody levels in specific geographic areas at different time points are needed to optimise policy responses. However, even population-wide surveys are potentially impacted by biases arising from differences in participation rates across key groups. Here, we use spatio-temporal regression and post-stratification models to UKs national COVID-19 Infection Survey (CIS) to obtain representative estimates of PCR positivity (6,496,052 tests) and antibody prevalence (1,941,333 tests) for different regions, ages and ethnicities (7-December-2020 to 4-May-2022). Not accounting for vaccination status through post-stratification led to small underestimation of PCR positivity, but more substantial overestimations of antibody levels in the population (up to 21%), particularly in groups with low vaccine uptake in the general population. There was marked variation in the relative contribution of different areas and age-groups to each wave. Future analyses of infectious disease surveys should take into account major drivers of outcomes of interest that may also influence participation, with vaccination being an important factor to consider.

Correlates of protection against SARS-CoV-2 Omicron variant and anti-spike antibody responses after a third/booster vaccination or breakthrough infection in the UK general population (preprint)

Following primary SARS-CoV-2 vaccination, understanding the relative extent of protection against SARS-CoV-2 infection from boosters or from breakthrough infections (i.e. infection in the context of previous vaccination) has important implications for vaccine policy. In this study, we investigated correlates of protection against Omicron BA.4/5 infections and anti-spike IgG antibody trajectories after a third/booster vaccination or breakthrough infection following second vaccination in 154,149 adults [≥]18y from the United Kingdom general population. We found that higher anti-spike IgG antibody levels were associated with increased protection against Omicron BA.4/5 infection and that breakthrough infections were associated with higher levels of protection at any given antibody level than booster vaccinations. Breakthrough infections generated similar antibody levels to third/booster vaccinations, and the subsequent declines in antibody levels were similar to or slightly slower than those after third/booster vaccinations. Taken together our findings show that breakthrough infection provides longer lasting protection against further infections than booster vaccinations. For example, considering antibody levels associated with 67% protection against infection, a third/booster vaccination did not provide long-lasting protection, while a Delta/Omicron BA.1 breakthrough infection could provide 5-10 months of protection against Omicron BA.4/5 reinfection. 50-60% of the vaccinated UK population with a breakthrough infection would still be protected by the end of 2022, compared to <15% of the triple-vaccinated UK population without previous infection. Although there are societal impacts and risks to some individuals associated with ongoing transmission, breakthrough infection could be an efficient immune-boosting mechanism for subgroups of the population, including younger healthy adults, who have low risks of adverse consequences from infection.

Detecting changes in population trends in infection surveillance using community SARS-CoV-2 prevalence as an exemplar (preprint)

BackgroundMonitoring infection trends is vital to informing public health strategy. Detecting and quantifying changes in growth rates can inform policymakers rationale for implementing or continuing interventions aimed at reducing impact. Substantial changes in SARS-CoV-2 prevalence with emergence of variants provides opportunity to investigate different methods to do this. MethodsWe included PCR results from all participants in the UKs COVID-19 Infection Survey between 1 August 2020-30 June 2022. Change-points for growth rates were identified using iterative sequential regression (ISR) and second derivatives of generalised additive models (GAMs). Consistency between methods and timeliness of detection were compared. FindingsOf 8,799,079 visits, 147,278 (1{middle dot}7%) were PCR-positive. Over the time period, change-points associated with emergence of major variants were estimated to occur a median 4 days earlier (IQR 0-8) in GAMs versus ISR, with only 2/48 change-points identified by only one method. Estimating recent change-points using successive data periods, four change-points (4/96) identified by GAMs were not found when adding later data or by ISR; 77% (74/96) of change-points identified by successive GAMs were identified by ISR. Change-points were detected 3-5 weeks after they occurred in both methods but could be detected earlier within specific subgroups. InterpretationChange-points in growth rates of SARS-CoV-2 can be detected in near real-time using ISR and second derivatives of GAMs. To increase certainty about changes in epidemic trajectories both methods could be run in parallel. Running either method in near real-time on different infection surveillance data streams could provide timely warnings of changing underlying epidemiology. FundingUK Health Security Agency, Department of Health and Social Care (UK), Welsh Government, Department of Health (on behalf of the Northern Ireland Government), Scottish Government, National Institute for Health Research.

Lineage replacement and evolution captured by the United Kingdom Covid Infection Survey (preprint)

The Office for National Statistics COVID-19 Infection Survey is a large household-based surveillance study based in the United Kingdom. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing sequenced samples collected up until 13th November 2021. We observed four distinct sweeps or partial-sweeps, by lineages B.1.177, B.1.1.7/Alpha, B.1.617.2/Delta, and finally AY.4.2, a sublineage of B.1.617.2, with each sweeping lineage having a distinct growth advantage compared to their predecessors. Evolution was characterised by steady rates of evolution and increasing diversity within lineages, but with step increases in divergence associated with each sweeping major lineage, leading to a faster overall rate of evolution and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens, particularly as routine PCR testing is phased out or in settings where large-scale sequencing is not feasible.

The challenge of limited vaccine supplies: impact of prior infection on anti-spike IgG antibody trajectories after a single COVID-19 vaccination (preprint)

Given high SARS-CoV-2 incidence, coupled with slow and inequitable vaccine roll-out, there is an urgent need for evidence to underpin optimum vaccine deployment, aiming to maximise global population immunity at speed. We evaluate whether a single vaccination in previously infected individuals generates similar initial and subsequent antibody responses to two vaccinations in those without prior infection. We compared anti-spike IgG antibody responses after a single dose of ChAdOx1, BNT162b2, or mRNA-1273 SARS-CoV-2 vaccines in the COVID-19 Infection Survey in the UK general population. In 100,849 adults who received at least one vaccination, 13,404 (13.3%) had serological and/or PCR evidence of prior infection. Prior infection significantly boosted antibody responses for all three vaccines, producing a higher peak level and longer half-life, and a response comparable to those without prior infection receiving two vaccinations. In those with prior infection, median time above the positivity threshold was estimated to last for >1 year after the first dose. Single-dose vaccination targeted to those previously infected may provide protection in populations with high rates of previous infection faced with limited vaccine supply, as an interim measure while vaccine campaigns are scaled up.

COVID-19 vaccination, risk-compensatory behaviours, and social contacts in four countries in the UK (preprint)

The physiological effects of vaccination against SARS-CoV-2 (COVID-19) are well documented, yet the behavioural effects are largely unknown. Risk compensation suggests that gains in personal safety, as a result of vaccination, are offset by increases in risky behaviour, such as socialising, commuting and working outside the home. This is potentially problematic because transmission of SARS-CoV-2 is driven by contacts, which could be amplified by vaccine-related risk compensation behaviours. Here, we show that social behaviours were overall unrelated to personal vaccination, but - adjusting for variation in mitigation policies - were responsive to the level of vaccination in the wider population: individuals in the UK were risk compensating when rates of vaccination were rising. This effect was observed across four nations of the UK, each of which varied policies autonomously.

SARS-CoV-2 anti-spike IgG antibody responses after second dose of ChAdOx1 or BNT162b2 in the UK general population (preprint)

We investigated anti-spike IgG antibody responses following second doses of ChAdOx1 or BNT162b2 SARS-CoV-2 vaccines in the UK general population. In 186,527 individuals, we found significant boosting of anti-spike IgG by second doses of both vaccines in all ages and using different dosing intervals, including the 3-week interval for BNT162b2. After second vaccination, BNT162b2 generated higher peak levels than ChAdOX1. Antibody levels declined faster at older ages than younger ages with BNT162b2, but were similar across ages with ChAdOX1. With both vaccines, prior infection significantly increased antibody peak level and half-life. Protection was estimated to last for 0.5-1 year after ChAdOx1 and >1 year after BNT162b2, but could be reduced against emerging variants. Reducing the dosing interval to 8 weeks for both vaccines or further to 3 weeks for BNT162b2 may help increase short-term protection against the Delta variant. A third booster dose may be needed, prioritised to more vulnerable people.

Monitoring populations at increased risk for SARS-CoV-2 infection in the community (preprint)

BackgroundThe COVID-19 pandemic is rapidly evolving, with emerging variants and fluctuating control policies. Real-time population screening and identification of groups in whom positivity is highest could help monitor spread and inform public health messaging and strategy. MethodsTo develop a real-time screening process, we included results from nose and throat swabs and questionnaires taken 19 July 2020-17 July 2021 in the UKs national COVID-19 Infection Survey. Fortnightly, associations between SARS-CoV-2 positivity and 60 demographic and behavioural characteristics were estimated using logistic regression models adjusted for potential confounders, considering multiple testing, collinearity, and reverse causality. FindingsOf 4,091,537 RT-PCR results from 482,677 individuals, 29,903 (0{middle dot}73%) were positive. As positivity rose September-November 2020, rates were independently higher in younger ages, and those living in Northern England, major urban conurbations, more deprived areas, and larger households. Rates were also higher in those returning from abroad, and working in healthcare or outside of home. When positivity peaked December 2020-January 2021 (Alpha), high positivity shifted to southern geographical regions. With national vaccine roll-out from December 2020, positivity reduced in vaccinated individuals. Associations attenuated as rates decreased between February-May 2021. Rising positivity rates in June-July 2021 (Delta) were independently higher in younger, male, and unvaccinated groups. Few factors were consistently associated with positivity. 25/45 (56%) confirmed associations would have been detected later using 28-day rather than 14-day periods. InterpretationPopulation-level demographic and behavioural surveillance can be a valuable tool in identifying the varying characteristics driving current SARS-CoV-2 positivity, allowing monitoring to inform public health policy. FundingDepartment of Health and Social Care (UK), Welsh Government, Department of Health (on behalf of the Northern Ireland Government), Scottish Government, National Institute for Health Research.

Secondary Attack Rates in Primary and Secondary School Bubbles Following a Confirmed Case: Active, Prospective National Surveillance, November to December 2020, England (preprint)

Background: Following the full re-opening of schools in England and emergence of the SARS-CoV-2 Alpha variant, we investigated the risk of SARS-CoV-2 infection in students and staff who were contacts of a confirmed case in a school bubble (school groupings with limited interactions), along with their household members. Methods: Primary and secondary school bubbles were recruited into sKIDsBUBBLE after being sent home to self-isolate following a confirmed case of COVID-19 in the bubble. Bubble participants and their household members were sent home-testing kits comprising nasal swabs for RT-PCR testing and whole genome sequencing, and oral fluid swabs for SARS-CoV-2 antibodies. Results: During November-December 2020, 14 bubbles were recruited from 7 schools, including 269 bubble contacts (248 students, 21 staff) and 823 household contacts (524 adults, 299 children). The secondary attack rate was 10.0% (6/60) in primary and 3.9% (4/102) in secondary school students, compared to 6.3% (1/16) and 0% (0/1) among staff, respectively. The incidence rate for household contacts of primary school students was 6.6% (12/183) and 3.7% (1/27) for household contacts of primary school staff. In secondary schools, this was 3.5% (11/317) and 0% (0/1), respectively. Household contacts were more likely to test positive if their bubble contact tested positive although there were new infections among household contacts of uninfected bubble contacts. Interpretation: Compared to other institutional settings, the overall risk of secondary infection in school bubbles and their household contacts was low. Our findings are important for developing evidence-based infection prevention guidelines for educational settings.

Impact of Delta on viral burden and vaccine effectiveness against new SARS-CoV-2 infections in the UK (preprint)

The effectiveness of BNT162b2, ChAdOx1, and mRNA-1273 vaccines against new SARS-CoV-2 infections requires continuous re-evaluation, given the increasingly dominant Delta variant. We investigated the effectiveness of the vaccines in a large community-based survey of randomly selected households across the UK. We found that the effectiveness of BNT162b2 and ChAd0x1 against any infections (new PCR positives) and infections with symptoms or high viral burden is reduced with the Delta variant. A single dose of the mRNA-1273 vaccine had similar or greater effectiveness compared to a single dose of BNT162b2 or ChAdOx1. Effectiveness of two doses remains at least as great as protection afforded by prior natural infection. The dynamics of immunity following second doses differed significantly between BNT162b2 and ChAdOx1, with greater initial effectiveness against new PCR-positives but faster declines in protection against high viral burden and symptomatic infection with BNT162b2. There was no evidence that effectiveness varied by dosing interval, but protection was higher among those vaccinated following a prior infection and younger adults. With Delta, infections occurring following two vaccinations had similar peak viral burden to those in unvaccinated individuals. SARS-CoV-2 vaccination still reduces new infections, but effectiveness and attenuation of peak viral burden are reduced with Delta.

Symptoms and SARS-CoV-2 positivity in the general population in the UK (preprint)

BackgroundSeveral community-based studies have assessed the ability of different symptoms to identify COVID-19 infections, but few have compared symptoms over time (reflecting SARS-CoV-2 variants) and by vaccination status. MethodsUsing data and samples collected by the COVID-19 Infection Survey at regular visits to representative households across the UK, we compared symptoms in new PCR-positives and comparator test-negative controls. ResultsFrom 26/4/2020-7/8/2021, 27,869 SARS-CoV-2 PCR-positive episodes occurred in 27,692 participants (median 42 years (IQR 22-58)); 13,427 (48%) self-reported symptoms ("symptomatic positive episodes"). The comparator group comprised 3,806,692 test-negative visits (457,215 participants); 130,612 (3%) self-reported symptoms ("symptomatic negative visit"). Reporting of any symptoms in positive episodes varied over calendar time, reflecting changes in prevalence of variants, incidental changes (e.g. seasonal pathogens, schools re-opening) and vaccination roll-out. There was a small increase in sore throat reporting in symptomatic positive episodes and negative visits from April-2021. After May-2021 when Delta emerged there were substantial increases in headache and fever in positives, but not in negatives. Although specific symptom reporting in symptomatic positive episodes vs. negative visits varied by age, sex, and ethnicity, only small improvements in symptom-based infection detection were obtained; e.g. adding fatigue/weakness or all eight symptoms to the classic four symptoms (cough, fever, loss of taste/smell) increased sensitivity from 74% to 81% to 90% but tests per positive from 4.6 to 5.3 to 8.7. ConclusionsWhilst SARS-CoV-2-associated symptoms vary by variant, vaccination status and demographics, differences are modest and do not warrant large-scale changes to targeted testing approaches given resource implications. SummaryWithin the COVID-19 Infection Survey, recruiting representative households across the UK general population, SARS-CoV-2-associated symptoms varied by viral variant, vaccination status and demographics. However, differences are modest and do not currently warrant large-scale changes to targeted testing approaches.

A cluster randomised trial of the impact of a policy of daily testing for contacts of COVID-19 cases on attendance and COVID-19 transmission in English secondary schools and colleges (preprint)

Summary Background School-based COVID-19 contacts in England are asked to self-isolate at home. However, this has led to large numbers of missed school days. Therefore, we trialled daily testing of contacts as an alternative, to investigate if it would affect transmission in schools. Methods We performed an open-label cluster randomised controlled trial in students and staff from secondary schools and further education colleges in England ( ISRCTN18100261 ). Schools were randomised to self-isolation of COVID-19 contacts for 10 days (control) or to voluntary daily lateral flow device (LFD) testing for school contacts with LFD-negative contacts remaining at school (intervention). Household contacts were excluded from participation. Co-primary outcomes in all students and staff were symptomatic COVID-19, adjusted for community case rates, to estimate within-school transmission (non-inferiority margin: <50% relative increase), and COVID-19-related school absence. Analyses were performed on an intention to treat (ITT) basis using quasi-Poisson regression, also estimating complier average causal effects (CACE). Secondary outcomes included participation rates, PCR results in contacts and performance characteristics of LFDs vs. PCR. Findings Of 99 control and 102 intervention schools, 76 and 86 actively participated (19-April-2021 to 27-June-2021); additional national data allowed most non-participating schools to be included in the co-primary outcomes. 2432/5763(42.4%) intervention arm contacts participated. There were 657 symptomatic PCR-confirmed infections during 7,782,537 days-at-risk (59.1/100k/week) and 740 during 8,379,749 days-at-risk (61.8/100k/week) in the control and intervention arms respectively (ITT adjusted incidence rate ratio, aIRR=0.96 [95%CI 0.75-1.22;p=0.72]) (CACE-aIRR=0.86 [0.55-1.34]). There were 55,718 COVID-related absences during 3,092,515 person-school-days (1.8%) and 48,609 during 3,305,403 person-school-days(1.5%) in the control and intervention arms (ITT-aIRR=0.80 [95%CI 0.53-1.21;p=0.29]) (CACE-aIRR 0.61 [0.30-1.23]). 14/886(1.6%) control contacts providing an asymptomatic PCR sample tested positive compared to 44/2981(1.5%) intervention contacts (adjusted odds ratio, aOR=0.73 [95%CI 0.33-1.61;p=0.44]). Rates of symptomatic infection in contacts were 44/4665(0.9%) and 79/5955(1.3%), respectively (aOR=1.21 [0.82-1.79;p=0.34]). Interpretation Daily contact testing of school-based contacts was non-inferior to self-isolation for control of COVID-19 transmission. COVID-19 rates in school-based contacts in both intervention and control groups were <2%. Daily contact testing is a safe alternative to home isolation following school-based exposures.

Anti-spike antibody response to natural SARS-CoV-2 infection in the general population (preprint)

We estimated the duration and determinants of antibody response after SARS-CoV-2 infection in the general population using representative data from 7,256 United Kingdom COVID-19 infection survey participants who had positive swab SARS-CoV-2 PCR tests from 26-April-2020 to 14-June-2021. A latent class model classified 24% of participants as non-responders not developing anti-spike antibodies. These seronegative non-responders were older, had higher SARS-CoV-2 cycle threshold values during infection (i.e. lower viral burden), and less frequently reported any symptoms. Among those who seroconverted, using Bayesian linear mixed models, the estimated anti-spike IgG peak level was 7.3-fold higher than the level previously associated with 50% protection against reinfection, with higher peak levels in older participants and those of non-white ethnicity. The estimated anti-spike IgG half-life was 184 days, being longer in females and those of white ethnicity. We estimated antibody levels associated with protection against reinfection likely last 1.5-2 years on average, with levels associated with protection from severe infection present for several years. These estimates could inform planning for vaccination booster strategies.

Impact of vaccination on SARS-CoV-2 cases in the community: a population-based study using the UK COVID-19 Infection Survey (preprint)

Objectives: To assess the effectiveness of COVID-19 vaccination in preventing SARS-CoV-2 infection in the community. Design: Prospective cohort study. Setting: The UK population-representative longitudinal COVID-19 Infection Survey. Participants: 373,402 participants aged [≥]16 years contributing 1,610,562 RT-PCR results from nose and throat swabs between 1 December 2020 and 3 April 2021. Main outcome measures: New RT-PCR-positive episodes for SARS-CoV-2 overall, by self-reported symptoms, by cycle threshold (Ct) value (<30 versus [≥]30), and by gene positivity (compatible with the B.1.1.7 variant versus not). Results: Odds of new SARS-CoV-2 infection were reduced 65% (95% CI 60 to 70%; P<0.001) in those [≥]21 days since first vaccination with no second dose versus unvaccinated individuals without evidence of prior infection (RT-PCR or antibody). In those vaccinated, the largest reduction in odds was seen post second dose (70%, 95% CI 62 to 77%; P<0.001).There was no evidence that these benefits varied between Oxford-AstraZeneca and Pfizer-BioNTech vaccines (P>0.9).There was no evidence of a difference in odds of new SARS-CoV-2 infection for individuals having received two vaccine doses and with evidence of prior infection but not vaccinated (P=0.89). Vaccination had a greater impact on reducing SARS-CoV-2 infections with evidence of high viral shedding Ct<30 (88% reduction after two doses; 95% CI 80 to 93%; P<0.001) and with self-reported symptoms (90% reduction after two doses; 95% CI 82 to 94%; P<0.001); effects were similar for different gene positivity patterns. Conclusion: Vaccination with a single dose of Oxford-AstraZeneca or Pfizer-BioNTech vaccines, or two doses of Pfizer-BioNTech, significantly reduced new SARS-CoV-2 infections in this large community surveillance study. Greater reductions in symptomatic infections and/or infections with a higher viral burden are reflected in reduced rates of hospitalisations/deaths, but highlight the potential for limited ongoing transmission from asymptomatic infections in vaccinated individuals. Registration: The study is registered with the ISRCTN Registry, ISRCTN21086382.

The impact of SARS-CoV-2 vaccines on antibody responses in the general population in the United Kingdom (preprint)

Real-world data on antibody response post-vaccination in the general population are limited. 45,965 adults in the UKs national COVID-19 Infection Survey receiving Pfizer-BioNTech or Oxford-AstraZeneca vaccines had 111,360 anti-spike IgG measurements. Without prior infection, seroconversion rates and quantitative antibody levels post single dose were lower in older individuals, especially >60y. Two doses achieved high responses across all ages, particularly increasing seroconversion in older people, to similar levels to those achieved after prior infection followed by a single dose. Antibody levels rose more slowly and to lower levels with Oxford-AstraZeneca vs Pfizer-BioNTech, but waned following a single Pfizer-BioNTech dose. Latent class models identified four responder phenotypes: older people, males, and those having long-term health conditions were more commonly low responders. Where supplies are limited, vaccines should be prioritised for those not previously infected, and second doses to individuals >60y. Further data on the relationship between vaccine-mediated protection and antibody responses are needed.

Ethnic differences in COVID-19 mortality during the first two waves of the Coronavirus Pandemic: a nationwide cohort study of 29 million adults in England (preprint)

Background Ethnic minorities have experienced disproportionate COVID-19 mortality rates in the UK and many other countries. We compared the differences in the risk of COVID-19 related death between ethnic groups in the first and second waves the of COVID-19 pandemic in England. We also investigated whether the factors explaining differences in COVID-19 death between ethnic groups changed between the two waves. Methods Using data from the Office for National Statistics Public Health Data Asset on individuals aged 30-100 years living in private households, we conducted an observational cohort study to examine differences in the risk of death involving COVID-19 between ethnic groups in the first wave (from 24 th January 2020 until 31 st August 2020) and second wave (from 1 st September to 28 th December 2020). We estimated age-standardised mortality rates (ASMR) in the two waves stratified by ethnic groups and sex. We also estimated hazard ratios (HRs) for ethnic-minority groups compared with the White British population, adjusted for geographical factors, socio-demographic characteristics, and pre-pandemic health conditions. Results The study population included over 28.9 million individuals aged 30-100 years living in private households. In the first wave, all ethnic minority groups had a higher risk of COVID-19 related death compared to the White British population. In the second wave, the risk of COVID-19 death remained elevated for people from Pakistani (ASMR: 339.9 [95% CI: 303.7 – 376.2] and 166.8 [141.7 – 191.9] deaths per 100,000 population in men and women) and Bangladeshi (318.7 [247.4 – 390.1] and 127.1 [91.1 – 171.3] in men and women)background but not for people from Black ethnic groups. Adjustment for geographical factors explained a large proportion of the differences in COVID-19 mortality in the first wave but not in the second wave. Despite an attenuation of the elevated risk of COVID-19 mortality after adjusting for sociodemographic characteristics and health status, the risk was substantially higher in people from Bangladeshi and Pakistani background in both the first and the second waves. Conclusion Between the first and second waves of the pandemic, the reduction in the difference in COVID-19 mortality between people from Black ethnic background and people from the White British group shows that ethnic inequalities in COVID-19 mortality can be addressed. The continued higher rate of mortality in people from Bangladeshi and Pakistani background is alarming and requires focused public health campaign and policy changes. *VN and NI contributed equally to this paper Research in context Evidence before this study A recent systematic review by Pan and colleagues demonstrated that people of ethnic minority background in the UK and the USA have been disproportionately affected by the Coronavirus (COVID-19) pandemic, compared to White populations. While several studies have investigated whether adjusting for socio-demographic and economic factors and medical history reduces the estimated difference in risk of mortality and hospitalisation, the reasons for the differences in the risk of experiencing harms from COVID-19 are still being explored during the course of the pandemic. Studies so far have analysed the ethnic differences in COVID-19 mortality in the first wave of the pandemic. The evidence on the temporal trend of ethnic inequalities in COVID-19 mortality, especially those from the second wave of the pandemic, is scarce. Added value of this study Using data from the Office for National Statistics (ONS) Public Health Data Asset on 29 million adults aged 30-100 years living in private households in England, we conducted an observational cohort study to examine the differences in the risk of death involving COVID-19 between ethnic groups in the first wave (from 24 th January 2020 until 31 st August 2020) and second wave (from 1 st September to 28 th December 2020). We find that in the first wave all ethnic minority groups were at elevated risk of COVID-19 related death compared to the White British population. In the second wave, the differences in the risk of COVID-19 related death attenuated for Black African and Black Caribbean groups, remained substantially higher in people from Bangladeshi background, and worsened in people from Pakistani background. We also find that some of the factors explaining these differences in mortality have changed in the two waves. Implications of all the available evidence The risk of COVID-19 mortality during the first wave of the pandemic was elevated in people from ethnic minority background. An appreciable reduction in the difference in COVID-19 mortality in the second wave of the pandemic between people from Black ethnic background and people from the White British group is reassuring, but the continued higher rate of mortality in people from Bangladeshi and Pakistani background is alarming and requires focused public health campaign and policy response. Focusing on treating underlying conditions, although important, may not be enough in reducing the inequalities in COVID-19 mortality. Focused public health policy as well as community mobilisation and participatory public health campaign involving community leaders may help reduce the existing and widening inequalities in COVID-19 mortality.

An external validation of the QCovid risk prediction algorithm for risk of mortality from COVID-19 in adults: national validation cohort study in England (preprint)

BackgroundTo externally validate a risk prediction algorithm (QCovid) to estimate mortality outcomes from COVID-19 in adults in England. MethodsPopulation-based cohort study using the ONS Public Health Linked Data Asset, a cohort based on the 2011 Census linked to Hospital Episode Statistics, the General Practice Extraction Service Data for pandemic planning and research, radiotherapy and systemic chemotherapy records. The primary outcome was time to COVID-19 death, defined as confirmed or suspected COVID-19 death as per death certification. Two time periods were used: (a) 24th January to 30th April 2020; and (b) 1st May to 28th July 2020. We evaluated the performance of the QCovid algorithms using measures of discrimination and calibration for each validation time period. FindingsThe study comprises 34,897,648 adults aged 19-100 years resident in England. There were 26,985 COVID-19 deaths during the first time-period and 13,177 during the second. The algorithms had good calibration in the validation cohort in both time periods with close correspondence of observed and predicted risks. They explained 77.1% (95% CI: 76.9% to 77.4%) of the variation in time to death in men in the first time-period (R2); the D statistic was 3.76 (95% CI: 3.73 to 3.79); Harrells C was 0.935 (0.933 to 0.937). Similar results were obtained for women, and in the second time-period. In the top 5% of patients with the highest predicted risks of death, the sensitivity for identifying deaths in the first time period was 65.9% for men and 71.7% for women. People in the top 20% of predicted risks of death accounted for 90.8% of all COVID-19 deaths for men and 93.0% for women. InterpretationThe QCovid population-based risk algorithm performed well, showing very high levels of discrimination for COVID-19 deaths in men and women for both time periods. It has the potential to be dynamically updated as the pandemic evolves and therefore, has potential use in guiding national policy. FundingNational Institute of Health Research RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSPublic policy measures and clinical risk assessment relevant to COVID-19 need to be aided by rigorously developed and validated risk prediction models. A recent living systematic review of published risk prediction models for COVID-19 found most models are subject to a high risk of bias with optimistic reported performance, raising concern that these models may be unreliable when applied in practice. A population-based risk prediction model, QCovid risk prediction algorithm, has recently been developed to identify adults at high risk of serious COVID-19 outcomes, which overcome many of the limitations of previous tools. Added value of this studyCommissioned by the Chief Medical Officer for England, we validated the novel clinical risk prediction model (QCovid) to identify risks of short-term severe outcomes due to COVID-19. We used national linked datasets from general practice, death registry and hospital episode data for a population-representative sample of over 34 million adults. The risk models have excellent discrimination in men and women (Harrells C statistic>0.9) and are well calibrated. QCovid represents a new, evidence-based opportunity for population risk-stratification. Implications of all the available evidenceQCovid has the potential to support public health policy, from enabling shared decision making between clinicians and patients in relation to health and work risks, to targeted recruitment for clinical trials, and prioritisation of vaccination, for example.

Correlation of Computerized Tomography (CT) Severity Score for COVID-19 pneumonia with Clinical Outcomes (preprint)

IntroductionVarious CT severity scores have already been described in literature since the start of this pandemic. One pertinent issue with all of the previously described severity scores is their relative challenging calculation and variance in inter-observer agreement. The severity score proposed in our study is relatively simpler, easier to calculate and apart from a trained radiologist, can easily be calculated even by physicians with good inter-observer agreement. Therefore, a rapid CT severity score calculation can give a clue to physician about possible clinical outcome without being dependent on radiologist who may not be readily available especially in third world countries. ObjectiveThe objective of this study is to develop a simple CT severity score (CT-SS) with good inter-observer agreement and access its correlation with clinical outcome. MethodsThis retrospective study was conducted by the Department of Radiology and Internal Medicine, at the Aga Khan University Hospital Karachi, from April 2020 to August 2020. Non-probability consecutive sampling was used to include all patients who were positive for COVID-19 on PCR, and underwent CT chest examination at AKUH. Severity of disease was calculated in each lobe on the basis of following proposed CT severity scoring system (CT-SS). For each lobe the percentage of involvement by disease was scored - 0% involvement was scored 0, <50% involvement was scored 1 and >50% involvement was scored 2. Maximum score for one lobe was 2 and hence total maximum overall score for all lobes was 10. Continuous data was represented using mean and standard deviation, and compared using independent sample t-tests. Categorical data was represented using frequencies and percentages, and compared using Chi-squared tests. Inter-observer reliability between radiologist and COVID intensivist for the 10 point CT-SS rated on 0-10 was assessed using the Kappa statistic. A p-value < 0.05 was considered significant for all analyses. ResultsA total of 73 patients were included, the majority male (58.9%) with mean age 55.8 {+/-} 13.93 years. The CT-SS rated on 0-10 showed substantial inter-observer reliability between radiologist and intensivist with a Kappa statistic of 0.78. Patients with CT-SS 8-10 had a significantly higher ICU admission & intubation rate (53.8% vs. 23.5%) and mortality rate (35.9% vs. 11.8%; p = 0.017), as compared to those with CT-SS 0-7. ConclusionWe conclude that the described CT severity score (CT-SS) is a quick, effective and easily reproducible tool for prediction of adverse clinical outcome in patients with COVID 19 pneumonia. The tool shows good inter-observer agreement when calculated by radiologist and physician independently.